“Shiro dreams of sushi” is a great documentary, about a perfectionist sushi chef in Tokyo who earned himself three Michelin stars. Really worth watching.

In that documentary, a food critic says that great chefs have the following five qualities

They take their work very seriously and consistently perform at the highest level

They aspire to improve their skills

Cleanliness

Impatience

They want things their way

He also says that what makes a great chef is to bring all of these attributes together.

This reminds me of Gladwell, who describes in his book Outliers that lots and lots of experience are often needed to be really successful. There is a certain air of perfectionism in the background, too. And interestingly, many great chefs or artists have learned their trait from scratch, even though they do now things that are really out of the box. The same holds for painters, for instance, like van Gogh or Picasso.

All this makes me wonder to what extent there is a connection to academia. Successful academics are very devoted, take their work very seriously and work very hard. They keep on learning, and they stay curious. They strive for perfection, they are ambitious. And it takes a long time and a lot of training until they are at that point (I still think that it really helps to be a good classical economist to do great work in behavioral economics. And that macroeconomists can benefit from micro theory and empirical skills.). Like it does for great chefs. So far so good.

As for impatience and stubbornness I’m less sure.

There is some impatience involved, but then, what makes an academic do good work seems to be to play the long game, to make sure that contributions are as good as they get. Attention to detail is important, and so is it not to rush. Now, if one thinks of impatience as being eager to move on, that may be true, and it may be related to academics often saying that they want time to do their research.

Last, stubbornness. Yes, academics sometimes want things their way, but what seems to be important is to strike a balance between that and what is useful to society and what the community values.

In the end of the day, there seems to be a connection to being a great chef I believe, even when it comes to those last two qualities. Academics do science for others, and the same holds for preparing a great meal. And if impatience means that one is looking forward to reaching perfection to finish a project before serving it to others, then that could fit too.

We’re sometimes accused of sitting in an ivory tower, feet up and writing in abstract terms about all kinds of things that are not directly relevant to the real world.

Well, there are academics like that, and there is certainly value to doing fundamental research that will be an important input more applied work done by others, but there are also many others.

For instance, they do consulting, and I have the impression that companies or institutions attach great value to this. There is nothing wrong with that, I believe, as long as it stays within limits and they keep doing research and keep teaching. To the contrary even, I see great potential that this will make them better teachers and researchers, because there teaching and research becomes more relevant to practice. Or they are involved in policy design and designing institutions within the scope of projects financed by third parties.

In a recent essay, Esther Duflo from the MIT has argued that attention to detail is not only interesting but really needed and useful. She suggests that economists should be more like plumbers. Worth reading, especially also for Ph.D. students who are making up their mind about the direction they want to go in.

I’ve earlier briefly described the benefits of using versioning software. In a nutshell, this is what professional coders use to collaborate and to keep track of changes they make to their code. Once you’ve set this up for conducting research projects, you usually don’t want to go back. See Gentzkow and Shapiro’s Practitioner’s guide for some guidance. Highly recommended!

I personally have used SVN for this, but over the last years Git has become more and more popular. I looked into it yesterday and it seems to me that it’s on the one hand more powerful than SVN and on the other hand easier to use. See for instance here for yourselves.

At Tilburg University, the role of the University Council is to represent the views of students and employees. I have now been serving for one two-year term and will serve for another one from September onwards.

This has not always been fun, believe me, but many people on campus don’t realize how much influence this council can have. And due to a teaching reduction that comes with the appointment I am able to stay a 100% scholar, even though I miss some of the teaching tasks, which is why I always viewed this engagement as temporary.

With our initiative TiU International, we have managed to bring a new perspective to the table, which inspired and resulted in a number of small steps that our university has taken—steps that go in the right direction if you ask us, and we feel broad support for this in the academic community.

For instance, our president and rector have said that they want to take the next step and produce most internal documents in English. One should not underestimate what this means: international employees (one in three academics is non-Dutch) will feel more at home, and slowly but surely we will thereby move towards also having a non-Dutch speaking dean, or non-Dutch speaking heads of departments (are there any at this point?). The underlying idea is that international employees and the diversity they add will help us make better decisions as an institution, at all levels, coming closer to achieving our goals. Why is that? They come from all over the world and have seen what works (and what doesn’t). Their experiences are therefore valuable also for us. And academia, to a large extent, is an international affair, and in the end of the day being internationally connected on all kinds of levels also benefits local, Dutch students and Dutch society.

Related to this, also a new language policy is in the making.

Besides, we have repeatedly argued that we have to change the real estate strategy, and that one-size-fits-all directives like the Tilburg Education Profile are misguided. If you ask me, then slowly but surely also these points are picked up. I find this already very motivating and rewarding.

So far for some examples of smaller steps.

But: we still have to think more about the big issues. To start with, what I’ve realized recently, more than anything else, is that there is actually no shared set of goals on campus (despite there being a strategy, formally). Different faculties have different goals.

And I think that this is actually fine, but needs to be acknowledged (in a revised strategy). So far, we have instead tried to unify, to come up with one strategy for the entire university (cf. the education profile). But we don’t need to have the same specific goals all across campus. Our faculties should strive for academic excellence, but importantly they should come up with their own interpretation of what that means. This includes excellent education.

At the same time, we need to define general principles that foster academic excellence. This could become an important part of our strategy in the end.

These should relate to what universities should be all about: creating and transferring knowledge.

For instance: promotions to full professor have to reflect academic performance, and not that somebody agreed to do an administrative task or has been around for long enough. Or brought in some money.

And there have to be no-go’s. People need to leave after their PhDs, and can only come back after having been offered tenure at an institution at least as good as ours. This is the international standard and ensures the young academics become independent of their former supervisors and also get a different perspective elsewhere. Long research visits can’t provide this.

And, in my view, professors are supposed to engage in both, research and teaching. Both inspire one another. But becoming professor should never be based only on performance in one of the two.

So far my thoughts in-between terms. I really hope we can get to discussing some of the big issues in the two years to come.

This, together with the smaller achievements, motivated me to run for a second time.

I just came across a nice article by Dan Hamermesh in a recent issue of the AER. It was discussed by Einav and Levin in another interesting publication in Science related to big data.

Einav and Levin write:

Hamermesh recently reviewed publications from 1963 to 2011 in top economics journals. Until the mid-1980s, the majority of papers were theoretical; the remainder relied mainly on “ready- made” data from government statistics or surveys. Since then, the share of empirical papers in top journals has climbed to more than 70%.

Isn’t that remarkable? I certainly was under the wrong impression when I was a Ph.D. student in Berkeley and Mannheim and thought that it’s all about theory and methods. Where does this come from? Maybe it was because one tends to see so much theory in the first year of a full-blown Ph.D. program, which is full of core courses in Micro, Macro and Econometrics, covering what is the foundation to doing good economic research. In any case, my advice to Ph.D. students would be to strongly consider working with real data, as soon as possible. There is certainly room for theoretical and methodological contributions, but this should not mean that one never touches data. At least in theory 😉 everybody should be able to do an empirical analysis. And for this, one has to practice early on. Even if one wants to do econometric theory in the end. But even then one should know what one is talking about. Or would you trust somebody who talks about cooking but never cooks himself? OK, I admit, this goes a bit too far.

After having said this let me speculate a bit. My personal feeling is that one of the next big things and maybe a good topic for a PhD could be to combine structual econometrics with some of the methods that are now used and developed in data science (see the Einav and Levin article along with Varian‘s nice piece). In Tilburg, for instance, we have a field course in big data, by the way, and another sequence in structural econometrics (empirical IO).

At the recent Netspar Pension Workshop I’ve been talking to Susann Rohwedder from the RAND Corporation. We talked about van Gogh and how he spent his youth in Brabant, not far away from Tilburg. The way he was painting at that time can be described as relatively dark and gloomy and not nearly as amazing as what he produced later in his life in the south of France, with the exception of the potato eaters, probably. Here, what dominates, arguably, is good craftsmanship. What I find remarkable is that he learned painting from scratch before moving on and developing something new.

Likewise, also Picasso first learned painting from scratch, producing paintings that were well done, but way more realistic that what he is known for now. Susann remarked that also for modern dancing people often say that one should first learn ballet dancing, in order to get a good grip on technical skills, before moving on. Interesting.

This discussion made me realize that there is a strong communality with my thinking about behavioral economics. There are many people who do research in behavioral economics without ever learning classical economics from scratch, and I always wondered why they do that. Standard economic theory is the simplest possible model we can think of, and it works just fine for many questions we may want to answer. There is of course lots to be gained by studying behavioral aspects of individual decision making, as recently demonstrated once more by Raj Chetty in his Ely lecture. But I think the best way to get there is to first fully understand classical economic theory and only then build on that. In passing, another thing that Chetty pointed out very nicely was that the best way to go about doing behavioral economics is probably not to point out where the classical theory is wrong—any model is wrong, because it abstracts from some aspects of economic behavior in order to focus on others—but to ask the question how we can use the insights from behavioral economics for policy making.

I always thought this was an awful book. I thought so because it sounded so egoistic to me. Win friends, influence people, all to one’s own advantage. What’s wrong with him?

Much to my surprise, I quite liked the book. As he explains, he did about 15 years of research before writing the book, and you can see it. It’s thorough, it’s well written, and it’s useful. And it’s not really egoistic. Of course in the end one benefits from it, but what I find nice is that others will benefit too, so it’s all about that. Somewhere towards the end he writes “The principles taught in this book will work only when they come from the heart. I am not advocating a bag of tricks. I am talking about a new way of life.”

It’s hard to summarize the book in a few sentences. What it’s basically about is to change one’s attitude towards other people, to praise them instead of criticising them, to become a better person, so that one is on the same page and achieves common goals together. In the end, we often have common goals with the IT department at work, with our students, our colleagues, and our bosses. And of course with our partners and families.

Carnegie goes through many examples and then spells out a number of principles that I could repeat here, but they actually only make sense in light of the examples and his explanations. Still, if you’re curious, then you can find them here. What I find fascinating is that the examples and the principles make so much sense—one can really see that a lot of thought went into them.

So what’s wrong with Dale Carnegie’s “How to win friends and influence people”? I think the title. A better one would probably be “How to be a good person and have success and happiness in life at the same time”. I really enjoyed it. Recommended reading.